FamilyBank
AI-powered financial literacy for families
I took a career break from software for about 10 years. When I decided to return, I enrolled in an MS in Software Engineering at Arizona State University.
By the time I graduated, AI had accelerated faster than I expected, and I realized I had to catch up there too. So I enrolled in an AI Product Management certification program.
For my capstone, the assignment only required a mockup and a slide deck. But I wanted to see if I could actually build it — not just present the idea. So I kept going and turned it into a real, shipped product.
I built FamilyBank.
FamilyBank is a financial literacy app for families with kids aged 6–16. Parents stay in control of the account — assigning chores with token rewards, approving completed chores, and approving wishlist purchases. Kids' only actions are marking a chore done and adding items to their wishlist, both of which require parent approval before anything actually happens. Kids earn tokens into 5 spending jars and track savings goals toward things they actually want. An AI coach gives age-appropriate lessons and quizzes to kids— and knows each child's real balance, goals, allowance schedule, and pending chores before every response, so the advice is personal and age-appropriate, not generic.
Live at: https://familybank.lovable.app/
Full stack: React + TypeScript + Supabase + Stripe + PWA + Web Push notifications. Multi-tenant auth with Row Level Security so families are fully isolated from each other. Stripe subscriptions with a 14-day trial. A full pre-launch security audit where I found and fixed real issues.
I used Lovable for AI-assisted development. I want to be upfront about that — but I made every product decision, wrote every prompt, designed every workflow, ran the security audit, and own the full architecture.
The product is live, security-audited, and pre-revenue right now — I'm focused on real user feedback before anything else.
Try it free for 14 days, no credit card required: https://familybank.lovable.app/ — would love your honest feedback on what's confusing, what's missing, and what you'd actually pay for.
4 Comments
Hey, just wanted to say — your product looks really impressive. It feels useful, clean, and like something that can actually help people solve a real problem.
I’m building Everyday Tiny Tools — a marketplace for small useful web tools, mini apps, calculators, generators, AI tools, productivity helpers, and simple utilities.
The idea is to give independent creators a real place to showcase their tools, get discovered, and maybe even earn from them.
If you’ve built something small and useful, I’d love to invite you to list it here: EverydayTinyTools.com
Tools can be listed as free, or as a simple one-time purchase through the platform.
And if you have any questions, feel free to reach out anytime: nuchem@lightboltlab.com
Really like what you’re building — wishing you a lot of success with it.
Really impressive journey from a capstone mockup to a live product.
One thing that stood out is that FamilyBank is combining financial literacy, behavior formation, parental control, and AI coaching in the same experience.
I'd be curious to see which part parents end up valuing enough to adopt first, because sometimes the thing founders build around and the thing users buy around end up being different.
Hi Aryan, I don’t have enough real usage data yet to say definitively which one parents will actually adopt around — that’s honestly part of why I’m sharing this here, to get more signal before I over-invest in any one direction. My plan right now is to watch which feature people return to most in their first week, rather than assume it’s the one I designed around.
Really appreciate you naming that distinction so clearly — “what founders build around vs. what users buy around” is a sharp way to put it, and I’m going to be thinking about that as I get more users in.
That's exactly the part I'd be careful with.
A lot of founders think they're waiting for more data when they're actually approaching a decision that shapes how they interpret the data they get.
I'd be careful unpacking that casually in a thread.
If you're interested, drop your email and I'll send over the fuller thought.